{"id":"https://openalex.org/W4312359105","doi":"https://doi.org/10.1109/iros47612.2022.9981323","title":"Dynamics-Aware Spatiotemporal Occupancy Prediction in Urban Environments","display_name":"Dynamics-Aware Spatiotemporal Occupancy Prediction in Urban Environments","publication_year":2022,"publication_date":"2022-10-23","ids":{"openalex":"https://openalex.org/W4312359105","doi":"https://doi.org/10.1109/iros47612.2022.9981323"},"language":"en","primary_location":{"id":"doi:10.1109/iros47612.2022.9981323","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros47612.2022.9981323","pdf_url":null,"source":{"id":"https://openalex.org/S4363607704","display_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061931648","display_name":"Maneekwan Toyungyernsub","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maneekwan Toyungyernsub","raw_affiliation_strings":["Stanford University,Stanford Intelligent Systems Laboratory (SISL),CA,USA","Stanford Intelligent Systems Laboratory (SISL), Stanford University, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University,Stanford Intelligent Systems Laboratory (SISL),CA,USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Stanford Intelligent Systems Laboratory (SISL), Stanford University, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014381337","display_name":"Esen Yel","orcid":"https://orcid.org/0000-0002-0463-3601"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Esen Yel","raw_affiliation_strings":["Stanford University,Stanford Intelligent Systems Laboratory (SISL),CA,USA","Stanford Intelligent Systems Laboratory (SISL), Stanford University, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University,Stanford Intelligent Systems Laboratory (SISL),CA,USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Stanford Intelligent Systems Laboratory (SISL), Stanford University, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100357080","display_name":"Jiachen Li","orcid":"https://orcid.org/0009-0005-2965-8468"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiachen Li","raw_affiliation_strings":["Stanford University,Stanford Intelligent Systems Laboratory (SISL),CA,USA","Stanford Intelligent Systems Laboratory (SISL), Stanford University, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University,Stanford Intelligent Systems Laboratory (SISL),CA,USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Stanford Intelligent Systems Laboratory (SISL), Stanford University, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068326377","display_name":"Mykel J. Kochenderfer","orcid":"https://orcid.org/0000-0002-7238-9663"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mykel J. Kochenderfer","raw_affiliation_strings":["Stanford University,Stanford Intelligent Systems Laboratory (SISL),CA,USA","Stanford Intelligent Systems Laboratory (SISL), Stanford University, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University,Stanford Intelligent Systems Laboratory (SISL),CA,USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Stanford Intelligent Systems Laboratory (SISL), Stanford University, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"10836","last_page":"10841"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/occupancy","display_name":"Occupancy","score":0.8189167380332947},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8033243417739868},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.6431124210357666},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6332751512527466},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6173806190490723},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4944193363189697},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.49241888523101807},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.451693058013916},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42454177141189575},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.39073485136032104},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.368630975484848},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36673080921173096},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09725061058998108}],"concepts":[{"id":"https://openalex.org/C160331591","wikidata":"https://www.wikidata.org/wiki/Q7075743","display_name":"Occupancy","level":2,"score":0.8189167380332947},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8033243417739868},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.6431124210357666},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6332751512527466},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6173806190490723},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4944193363189697},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.49241888523101807},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.451693058013916},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42454177141189575},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.39073485136032104},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.368630975484848},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36673080921173096},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09725061058998108},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros47612.2022.9981323","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros47612.2022.9981323","pdf_url":null,"source":{"id":"https://openalex.org/S4363607704","display_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.8299999833106995}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W569478347","https://openalex.org/W1512921847","https://openalex.org/W1999050017","https://openalex.org/W2029724021","https://openalex.org/W2031489346","https://openalex.org/W2145021371","https://openalex.org/W2653246566","https://openalex.org/W2796873224","https://openalex.org/W2962721463","https://openalex.org/W2963440325","https://openalex.org/W2963589995","https://openalex.org/W2967033144","https://openalex.org/W2968337686","https://openalex.org/W2990956645","https://openalex.org/W3034486798","https://openalex.org/W3035172746","https://openalex.org/W3093434340","https://openalex.org/W3161855852","https://openalex.org/W3205945099","https://openalex.org/W4206055888","https://openalex.org/W4310895557","https://openalex.org/W6628877408","https://openalex.org/W6713563955","https://openalex.org/W6750259706"],"related_works":["https://openalex.org/W4282043467","https://openalex.org/W2105697914","https://openalex.org/W3093197249","https://openalex.org/W1968324288","https://openalex.org/W1540010871","https://openalex.org/W3023979140","https://openalex.org/W3177545769","https://openalex.org/W2904068067","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"Detection":[0],"and":[1,27,52,59,86,110],"segmentation":[2,85],"of":[3,9,14,68,78,81],"moving":[4,54],"obstacles,":[5],"along":[6],"with":[7],"prediction":[8,88,113],"the":[10,15,39,57,65,69,76,97,105],"future":[11],"occupancy":[12],"states":[13],"local":[16],"environment,":[17],"are":[18],"essential":[19],"for":[20],"autonomous":[21,72],"vehicles":[22],"to":[23,63,74],"proactively":[24],"make":[25],"safe":[26],"informed":[28],"decisions.":[29],"In":[30],"this":[31,61],"paper,":[32],"we":[33,90],"propose":[34,91],"a":[35],"framework":[36],"that":[37],"integrates":[38],"two":[40],"capabilities":[41],"together":[42],"using":[43,92],"deep":[44],"neural":[45],"network":[46],"architectures.":[47],"Our":[48,100],"method":[49,101],"first":[50],"detects":[51],"segments":[53],"objects":[55],"in":[56],"scene,":[58],"uses":[60],"information":[62],"predict":[64],"spatiotemporal":[66],"evolution":[67],"environment":[70,87,94],"around":[71],"vehicles.":[73],"address":[75],"problem":[77],"direct":[79],"integration":[80],"both":[82],"static-dynamic":[83],"object":[84],"models,":[89],"occupancy-based":[93],"representations":[95],"across":[96],"whole":[98],"framework.":[99],"is":[102],"validated":[103],"on":[104],"real-world":[106],"Waymo":[107],"Open":[108],"Dataset":[109],"demonstrates":[111],"higher":[112],"accuracy":[114],"than":[115],"baseline":[116],"methods.":[117]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}